Chengfang Lu
e72bc061c5
Major changes: - New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind - 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理 - Data catalog with charts (DMS/ADAS/Lane 3-tab view) - Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance - Audit enhancements: batch operations, rejection categories, Feishu notifications - Operation audit log (操作日志) - World model simulation studio (仿真工坊) - Dataset version management with snapshots and diff - ADAS 7-class dataset integration (138K images organized + compressed) - User management with Feishu integration and pagination - CRUD/search/filter on all pages, card layout redesign - PIL-optimized image overlay rendering - Auto-snapshot on build, in_review workflow stage - Removed embedded algorithm code (now in workspace)
78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
import torch
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import argparse
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try:
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from utils.common import warnings
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except ImportError:
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import warnings
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# Beware of memory leaks! https://pytorch.org/docs/1.6.0/multiprocessing.html#sharing-strategies
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# torch.multiprocessing.set_sharing_strategy('file_system')
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from utils.args import parse_arg_cfg, read_config, map_states, add_shortcuts, cmd_dict
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from utils.runners import LaneDetTrainer, LaneDetTester
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if __name__ == '__main__':
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# ulimit
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try:
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import resource
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rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
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dest = 8192
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try:
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resource.setrlimit(resource.RLIMIT_NOFILE, (dest, rlimit[1]))
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except ValueError:
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warnings.warn(
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'Unable to set a high enough file descriptor limit {} (your system may has a low hard limit {}). ' \
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'If you encounter related problems in training, try reduce the number of workers by --workers, ' \
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'or switch into file_system mode at Line 8.'.format(dest, rlimit[1]))
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except ModuleNotFoundError:
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warnings.warn('Are you using Windows? Linux is recommended.')
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# Settings (user input > config > argparse defaults)
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parser = argparse.ArgumentParser(description='PytorchAutoDrive Lane Detection', conflict_handler='resolve')
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add_shortcuts(parser)
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# Required args
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parser.add_argument('--config', type=str, help='Path to config file', required=True)
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group = parser.add_mutually_exclusive_group(required=True)
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group.add_argument('--train', action='store_true')
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group.add_argument('--test', action='store_true')
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group.add_argument('--val', action='store_true')
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group.add_argument('--fastval', action='store_true')
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group.add_argument('--state', type=int,
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help='[Deprecated] validation(3)/final test(2)/fast validation(1)/training(0)')
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# Optional args/to overwrite configs
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group2 = parser.add_mutually_exclusive_group()
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group2.add_argument('--continue-from', type=str,
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help='[Deprecated] Continue training from a previous checkpoint')
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group2.add_argument('--checkpoint', type=str,
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help='Continue/Load from a previous checkpoint')
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parser.add_argument('--mixed-precision', action='store_true',
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help='Enable mixed precision training')
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parser.add_argument('--cfg-options', type=cmd_dict,
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help='Override config options with \"x1=y1 x2=y2 xn=yn\"')
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states = ['train', 'fastval', 'test', 'val']
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retain_args = ['state', 'mixed_precision']
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args = parser.parse_args()
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if args.state is not None:
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warnings.warn('--state={} is deprecated, it is recommended to specify with --{}'.format(
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args.state, states[args.state]))
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args.state = map_states(args, states)
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if args.mixed_precision and torch.__version__ < '1.6.0':
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warnings.warn('PyTorch version too low, mixed precision training is not available.')
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# Parse configs and execute runner
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cfg = read_config(args.config)
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cfg_runner_key = 'train' if args.state == 0 else 'test'
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Runner = LaneDetTrainer if args.state == 0 else LaneDetTester
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args, cfg = parse_arg_cfg(args, cfg)
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for k in retain_args:
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cfg[cfg_runner_key][k] = vars(args)[k]
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runner = Runner(cfg=cfg)
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runner.run()
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runner.clean()
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